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metric.py
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"""
Hidden Markov Model for Temporal Graphs
File: metric.py
Authors: Federico Errica (federico.errica@neclab.eu)
Alessio Gravina (alessio.gravina@phd.unipi.it)
Davide Bacciu (davide.bacciu@unipi.it)
Alessio Micheli (alessio.micheli@unipi.it)
<NAME OF B (email B)>
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"""
from typing import List, Tuple
import torch
from pydgn.training.callback.metric import Metric
class HMM4GLoss(Metric):
@property
def name(self) -> str:
return 'HMM4G E-step Objective'
def on_backward(self, state):
pass
def get_predictions_and_targets(self, targets: torch.Tensor, *outputs: List[torch.Tensor]) -> Tuple[
torch.Tensor, torch.Tensor]:
return outputs[2], outputs[2]
def compute_metric(self, targets: torch.Tensor, predictions: torch.Tensor) -> torch.tensor:
return predictions.mean()
class HMM4GLogLikelihood(Metric):
@property
def name(self) -> str:
return 'HMM4G Log Likelihood'
def on_backward(self, state):
pass
def get_predictions_and_targets(self, targets: torch.Tensor, *outputs: List[torch.Tensor]) -> Tuple[
torch.Tensor, torch.Tensor]:
return outputs[3], outputs[3]
def compute_metric(self, targets: torch.Tensor, predictions: torch.Tensor) -> torch.tensor:
return predictions.mean()